Provided is a method for diagnosing cancer through a difference with a control group in view of the ratio of a deglycosylated peptide fragment and a non-glycosylated peptide fragment in a protein including an N-linked glycosylation motif. Further provided is a method for diagnosing cancer through the detection of the glycosylation ratio in the protein according to the subject matter enables the diagnosis of cancer with high specificity and sensitivity using at least one existing marker, and can be useful in discovering new markers for diagnosing cancer.
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1. A method of diagnosing a liver cancer in a subject or a sample in need thereof comprising the steps of:
providing a biological sample from the subject comprising proteins having a N-linked glycosylation motif;
de-glycosylating the proteins comprised in the sample;
fragmenting the de-glycosylated proteins to obtain de-glycosylated peptides comprising the N-linked motif, and non-glycosylated peptides comprising a non-glycosylated motif and which do not comprise the N-linked motif;
determining in the fragmented proteins an amount of the de-glycosylated peptide at the N-linked motif and the amount of a non-glycosylated peptide which does not contain the N-linked motif and a ratio of the amount of the de-glycosylated peptide to the non-glycosylated peptide; and
diagnosing the subject or the sample as the cancer or susceptible to the cancer if the ratio is changed in the subject or in the sample compared to that of a control,
wherein the proteins, the peptide fragments from the proteins which are de-glycosylated at the N-linked glycosylation motif, the de-glycosylated peptide and the non-glycosylated peptide of the proteins are at least one as listed in Table 1; and the amount is determined using a LC-MS obtained by SIM (Selected Ion Monitoring) or MRM (Multiple reaction monitoring).
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The present application is a national stage application of International Patent Application No. PCT/KR2014/006479, filed Jul. 17, 2014, and claims the benefit of Korean Patent Application No. 2013-0088006, filed Jul. 25, 2013 in the Korean Intellectual Property Office, the disclosure of which are incorporated herein.
The Sequence Listing submitted in text format (.txt) filed on Jul. 17, 2017, named “SequenceListing.txt”, created on Jul. 17, 2017 (35.9 KB), is incorporated herein by reference.
The present disclosure generally relates to biomarkers and cancer diagnosis using the same, particularly diagnosis or detection of liver cancer.
Biomarkers are widely used to diagnosis various diseases including cancer in which the early detection or diagnosis is crucial for the successful treatment or the accurate diagnosis is difficult with conventional methods. Nucleic acid molecules or proteins are two commonly used types of biomarkers with which the expression levels or any changes in the amount are used as parameters for diagnosis. Recently post-translational modifications of proteins have been developed as biomarkers and one of them is to detect the glycosylation of proteins.
Thus methods have been developed to detect or analyze the changes or differences in the glycosylation levels of proteins. For example, glycoproteins are hydrolyzed to release glycans, which are then collected to profile the glycosylation status (Cooke C. L. et al., Anal. Chem., 2007, 79:8090-8097). Although such methods can be used to differentiate a healthy person from a patient, they have limitations in that various information such as specific information on the glycosylated proteins, positons of the glycosylation and isoforms are required for an accurate diagnosis.
Korean Patent Publication No. 2012-0125157 relates to biomarkers and methods to diagnosis cancer using the information on the aberrant glycosylation and discloses steps of isolating proteins abnormally glycosylated during the development or progression of cancers using lectins, and selecting and quantifying marker peptides generated from the hydrolysis of the isolated glycosylated proteins.
Korean Patent Publication No. 2010-0120788 relates to methods to diagnose a cancer using the glycosylation of proteins and discloses the use of specific changes in the hydrolysis pattern of particular peptides for the diagnosis of cancer.
However the glycosylation of proteins in patients with cancer or cured of cancer may occur at various amino acids residues such as aspargine, threonine, or serine and the like as in healthy patients. Thus, the specific glycosylation patterns or structure associated with a particular cancer may occur at one of the residues as above and coexist with the glycosylation found in normal cases leading to a microheterogeneity. Therefore the specific glycosylation associated with a particular cancer is present in a minute amount relative to a total amount of proteins, existing as a part of many glycan-isoforms found in any one of the residues. This requires a development of a more sensitive and specific methods for a reliable measurement of the glycosylation changes associated with a particular cancer.
The present disclosure is to provide a method of diagnosing cancer with a high specificity and sensitivity in a noninvasive way by determining the glycosylated ratio of proteins, biomarkers used therefor and a method of screening biomarkers.
In one aspect, the present disclosure provides a method of detecting marker in vitro to provide information for diagnosing or prognosis of cancer in a subject or a sample in need thereof comprising the steps of: providing a sample from the subject comprising proteins having a N-linked glycosylation motif; de-glycosylating the proteins comprised in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptide at the N-linked motif and the amount of the non-glycosylated peptide which does not contain the N-linked motif and the ratio therebetween; and diagnosing the subject or the sample as cancer or susceptible to cancer if the ratio is changed in the subject or in the sample compared to that of a control.
In other aspect, the present discourse provides a method of detecting, diagnosing or prognosis of cancer in a subject or a sample in need thereof comprising the steps of: providing a sample from the subject comprising proteins having a N-linked glycosylation motif; de-glycosylating the proteins comprised in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptide at the N-linked motif and the amount of the non-glycosylated peptide which does not contain the N-linked motif and the ratio therebetween; and diagnosing the subject or the sample as cancer or susceptible to cancer if the ratio is changed in the subject or in the sample compared to that of a control.
In still other aspect, the present disclosure provides a method of appraise or evaluating a cancer sample, in need thereof comprising the steps of: providing a sample from the subject comprising proteins having a N-linked glycosylation motif; de-glycosylating the proteins comprised in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptide at the N-linked motif and the amount of the non-glycosylated peptide which does not contain the N-linked motif and the ratio therebetween; and diagnosing the subject or the sample as cancer or susceptible to cancer if the ratio is changed in the subject or in the sample compared to that of a control. The methods are particularly performed in vitro to diagnose and/or prognosis of cancer and/or monitoring the therapeutic efficacy of the treatments and/or to determine the therapeutic regimes.
In the present methods, the values or ratios of the control samples may be determined or obtained in advance of the present methods are performed or may be determined during the present methods are performed.
In one embodiment of the present disclosure, the N-linked glycosylation motif is represented by the amino acid sequence of AsnXxxSer (SEQ ID NO: 3), AsnXxxThr (SEQ ID NO: 4) (or NxS/T) or AsnXxxCys (SEQ ID NO: 5), which are detected as AspXxxSer (SEQ ID NO: 6), AspXxxThr (SEQ ID NO: 7) and AspXxxCys (SEQ ID NO: 8), respectively when deglycosylated.
The de-glycosylation step may be performed using various methods known in the art including an enzyme. For example, the deglycosylation may be performed using PNGase-F, but is not limited thereto. The fragmentation of the present methods may be performed using various methods known in the art including for example a trypsin, a lysine-C, an arginine-C or an aspartic acid N without being limited thereto.
The present methods may be applied to determine or detect or diagnose or monitoring various cancers such as a blood cancer, a liver cancer, a stomach cancer, a colon cancer, a lung cancer, a uterine cancer, a breast cancer, a prostate cancer, a thyroid cancer and a pancreatic cancer without being limited thereto.
The samples comprising NxS/T motif which may be employed for the present methods includes at least one of a cell, a whole blood, a serum, a plasma, a saliva, a urine, a follicular fluid, a breast milk and a pancreatin without being limited thereto.
In the present methods, for the quantification of the peptides, a Mass spectrometry such as LC-MS (Liquid chromatography spectrometry) may be employed without being limited thereto. And the data from LC-MS may be obtained using Selected Ion Monitoring (SIM) or Multiple reaction monitoring (MRM). Further the determination of the amount using the MRM may be performed by monitoring a m/z value and optimized collision energy as described in the present Examples.
In the present methods, the protein having an N-linked motif may be a protein known in the art in relation to a particular disease. In one embodiment, AFP (alpha feto protein) is used and in which case the de-glycosylated peptide may be VDFTEIQK (SEQ ID NO: 9), and the non-glycosylated peptide may be GYQELLEK (SEQ ID NO: 10). The exact sequence to be detected may be various as long as they comprise NxS/T motif.
In other embodiment, the test protein sample having NxS/T motif to be analyzed is from liver cancer patient, and is blood, and may include ones listed in Table 1 disclosed herein. The de-glycosylated and non-glycosylated peptides corresponding to each protein of Table 1 may include ones listed in Table 1. However, the specific proteins and the corresponding peptides may be various for example depending on the particular methods of quantification employed and/or conditions thereof.
In other aspect, the present disclosure also provides a kit for diagnosis or prognosis of a cancer used for any one of the methods of the present disclosure, the kit comprising a first enzyme de-glycosylating a protein having a AsnXxxSer (SEQ ID NO: 3)/Thr motif, a second enzyme fragmenting the protein, and an agent for quantifying the de-glycosylated and the non-glycosylated peptides.
The present methods can be advantageously used for diagnosis or prognosis or monitoring cancer with a high specificity and sensitivity by measuring the glycosylation ratio of the conventional markers. Also the present methods can be advantageously used to screen markers for cancer diagnosis. Particularly, by using MRM LC-MS in which LC-Mass are combined with Triple quadrupole (QQQ), the total analysis time is very short as 10-15 min and thus the present methods can be efficiently employed for diagnosis of multiple samples.
Also, the present methods can be applied to discover additional markers from the glycoproteins having a higher specificity or sensitivity than the conventional markers, which can be used advantageously to diagnose, monitor the cancer or determine the stages of the cancer. Also the biomarkers and the methods of the present disclosure employed in the glycosylation analysis provides a simple and non-invasive way of diagnose or monitoring cancer using blood as sample.
The foregoing summary is illustrative only and is not intended to be in any way limiting. Additional aspects and/or advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
These and/or other aspects and advantages of the invention will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
The present disclosure is based on the findings that the level of glycosylation of proteins in comparison to non-glycosylated proteins occurring during the post translational modification can be used effectively to diagnose cancers.
In one aspect of the present disclosure, there is provided a method of diagnosing or prognosis of cancer, or monitoring the progress of the therapy or the state the cancer in a subject or a sample in need thereof comprising steps of: providing a biological sample from the subject, the sample comprising proteins having a N-linked glycosylation motif; de-glycosylating the proteins comprised in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptides at the N-linked motif and the amount of the non-glycosylated peptides at a non N-linked motif and the ratio of the glycosylated peptide to the non-glycosylated peptide; and diagnosing the subject or the sample as cancer or susceptible to cancer if the ratio is changed in the subject compared to that of a normal control.
In other aspect of the present disclosure, there is provided a method of assess or diagnose a sample from a cancer patient or a patient suspected of cancer, comprising steps of: providing a sample from a cancer patient or a patient suspected of cancer comprising proteins having a N-linked glycosylation motif; de-glycosylating the proteins comprised in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptides at the N-linked motif and the amount of the non-glycosylated peptides at a non N-linked motif and the ratio of the glycosylated peptide to the non-glycosylated peptide; and diagnosing the sample as cancer or susceptible to cancer if the ratio is changed in the sample compared to that of a normal control. The present methods may be performed in vitro and/or in vivo. In one embodiment, the method is performed in vitro to diagnose and/or prognosis of cancer, and/or monitoring the progress or the status of a subject to provide the information on the efficacy of treatment, and/or selecting optimal therapy regimes.
In the present disclosure, the value determined in a normal control which is used to compare to that of a cancer sample may be a value determined during or before the method is performed.
Proteins undergo post translational modification (PTM) after translation to become functional. Among PTM, glycosylation plays an important role in various cellular process or properties of the proteins such as half-lives, cell-cell interaction and antigenic properties of the proteins. Glycosylation is the enzyme catalyzed process in contrast to non-enzymatic glycation process, and during the process sugars are added to proteins to form glycan chains.
Included in the types of Glycosylation are N-linked glycosylation, O-linked glycosylation, C-mannosylation and GPI (glycophosphatidyl-inositol) anchor attachment. Encompassed in the present disclosure is N-linked glycosylation.
By N-linked glycosylation, glycan is attached to Asparagine residue at the same time with a translation affecting protein folding. N-linked glycosylation occurs at a particular peptide motif including Asn-Xxx-Ser (SEQ ID NO: 3)/Thr(N-X-S/T) or Asn-Xxx-Cys (SEQ ID NO: 5) (N-X-C), in which Xxx refers to any amino acids except proline. The proteins comprised in the present biological sample comprise N-linked glycosylation motifs at all or part of which the proteins are glycosylated. As diseases such as cancer develops or progresses, the amount of proteins expressed and/or the level of glycosylation and a particular type of sugar for example fucose is attached.
In the present disclosure, the biological samples from a patient or a normal control employed in the present methods comprise N-linked glycosylation motif. The samples to be tested are from patients who have a cancer or who are suspected of having cancer or who are in need of a cancer diagnosis or who are undergoing cancer therapy or who are cured of cancer. As a control, biological samples from a normal subject or a subject cured of cancer may be used. In the present disclosure, the subject includes mammals, particularly humans.
In accordance of the present disclosure, not only biological samples from appropriate patients but also proteins extracted from the sample are included. In one embodiment, the samples embodied in the present disclosure are a biological sample obtained from an organism including proteins from which information related to disease such as cancer development or progress or status can be determined or detected. Such samples include biological tissues, cell lines obtained by culturing biological tissues or media from the culture cells, cells, whole blood, serum, plasma, saliva, urine, cerebro-spinal fluid, liquor folliculi, milk and pancreatin, but are not limited thereto. Particularly glycoproteins related to cancer development or progress of the disease are released from the cells into the blood or extracellular fluids and thus bloods from the patient/subject to be tested or culture media in which cancer cells have been cultured can be advantageously used for detecting glycoproteins. In case of blood, the concentrations of proteins comprised therein varies widely among them. Thus, the samples may be pretreated to remove abundant proteins using a column such as MARS (Multiple Affinity Removal System) and the like. However the pretreatment may be omitted if the sensitivity and reproducibility of the target protein detection is not affected.
Particularly, many kinds of monosaccharides present on the surface of the cell membrane and they move inside the cell membrane by a signal transduction and are enzymatically transferred to proteins in the membrane by N-acetylglucosaminyltransferase to produce glycosylated proteins. The glycoproteins then perform their cellular function. Many glycoproteins present on the cell surface undergo abnormal glycosylation by particular signals generated from such as oncogenes. It has been known that abnormal function of glycosyltransferases and glycolytic enzymes due in response to the signal by oncogenes are involved in the cancer development (Kim, Y. J., et al., Glycoconj. J., 1997, 14, 569-576., Hakomori, S., Adv. Cancer Res., 1989, 52, 257-331., Hakomori, S., Cancer Res., 1996, 56, 5309-5318).
In the present methods, the ratio of glycosylated proteins to non-glycosylated proteins at a particular motif is determined and that is used to diagnose and/or prognosis and/or monitor various cancers in which glycosylation is associated with the development or progression of cancer. For example, such cancers include blood cancer, liver cancer, colon cancer, lung cancer, uterine cancer, breast cancer, prostate cancer, thymus cancer and pancreatic cancer but are not limited thereto. The term diagnosis as used herein refers to determining susceptibility of a subject to a disease or disorder, determining whether a subject has a specific disease or disorder, determining the prognosis (for example, identification of transitional cancer status, stages or progression of a cancer or determining the response to cancer treatments) of a subject who has a particular disease or disorder, or therametrics (for example, monitoring the status of a subject to provide the information on the efficacy of treatment).
In accordance with the present methods, the level of de-glycosylated motif at the glycosylation motif and the level of non-glycosylation motif and its ratio are determined, which is then compared to the values obtained from a normal control. In comparison to the control, when the ratio is changed, i.e., decreased or increased, in the subject or in the sample, the ratios are used to diagnose, prognosis or detect cancer, or monitor the stages or progression of cancer. The levels may be determined as described hererinafter. When liquid chromatographic methods are used, the area of the peak corresponding to de-glycosylated fragments and the area of the peak corresponding to non-glycosylation fragments are determined, which are then used to calculate the ratios after normalization of each of the peak area above with that of the internal standard peptide, i.e., to calculate the normalized peak area of the de-glycosylated fragment/the normalized peak area of the non-glycosylated fragment.
Therefore, to de-glycosylate the glycosylation motif and fragment them, various de-glycosylation enzymes known in the art may be employed for the present methods. In one embodiment, PNGase-F (Peptide N Glycosidase F) is used. In the present methods, the proteins in the sample are fragmented into polypeptides of 6-24 amino acids in length. For this, various hydrolytic enzymes may be employed, which include for example trypsin that digest amide bond between lysine and arginine. Also lysine-C that hydrolyzes at a lysine residue, arginine-C that hydrolyzes at an arginine residue, an aspartic acid N that hydrolyzes at an aspartic acid may also be used as desired. In one embodiment, a trypsin is used.
The non-glycosylation motif employed in the present methods is an amino acid sequence which is not glycosylated and found in the same protein as the glycosylation motif is found. The non-glycosylation motif does not contain NxS/T motif, cysteine as well as methionine. The length of the non-glycosylation motif may vary depending on the detection methods employed. For example, when the mass spectrometry is used, the peptide length of about 5 to about 24 amino acids may be selected and used in consideration of the detection range which is about 15-1400 m/z, average molecular weight and charge of an amino acid, and a minimum length conferring specificity. But the length is not limited thereto.
In one embodiment, the glycosylation and non-glycosylation motifs are selected from the proteins which may be used as a diagnostic marker of liver cancer such as AFP, SERPINF2, A2M, APOB, GLB1, BMP1, SERPINA6, CFH, BCHE, CLU, COL12A1, CPN2, VCAN, ERBB3, F5, F11, AFP, FSTL1, GNS, GPR126, SERPIND1, HYOU1, ITGA2, ITGA3, ITGA6, ITGAM, ITGB2, KLKB1, KTN1, LAMP2, LGALS3BP, PLXNA1, POSTN, PTK7, ROBO4, TNC, or VTN. The de-glycosylated peptide which is generated by the de-glycosylation of glycosylation peptide, and the non-glycosylation motifs are as disclosed in Table 1. More than one peptide may be selected.
TABLE 1
Protein Marker
De-glycosylated peptide
Non-glycosylation peptide
AFP
VDFTEIQK (SEQ ID NO: 9)
GYQELLEK (SEQ ID NO: 10)
SERPINF2
NPDPSAPR (SEQ ID NO: 11)
LGNQEPGGQTALK (SEQ ID NO: 12)
A2M
VSDQTLSLFFTVLQDVPVR (SEQ ID
AIGYLNTGYQR (SEQ ID NO: 14)
NO: 13)
FEVQVTVPK (SEQ ID NO: 15)
IAQWQSFQLEGGLK (SEQ ID NO: 16)
NEDSLVFVQTDK (SEQ ID NO: 17)
VSVQLEASPAFLAVPVEK (SEQ ID NO: 18)
APOB
FEVDSPVYDATWSASLK (SEQ ID
LSLESLTSYFSIESSTK (SEQ ID NO: 20)
NO: 19)
GLB1
NNVITLDITGK (SEQ ID NO: 21)
VNYGAYINDFK (SEQ ID NO: 22)
BMP1
IILDFTSLDLYR (SEQ ID NO: 23)
GIFLDTIVPK (SEQ ID NO: 24)
SERPINA6
AQLLQGLGFDLTER (SEQ ID NO: 25)
ITQDAQLK (SEQ ID NO: 26)
WSAGLTSSQVDLYIPK (SEQ ID NO: 27)
CFH
SPDVIDGSPISQK (SEQ ID NO: 28)
SSIDIENGFISESQYTYALK (SEQ ID NO: 29)
BCHE
WSDIWDATK (SEQ ID NO: 30)
AILQSGSFNAPWAVTSLYEAR (SEQ ID NO: 31)
IFFPGVSEFGK (SEQ ID NO: 32)
YLTLNTESTR (SEQ ID NO: 33)
CLU
LADLTQGEDQYYL (SEQ ID NO: 34)
ASSIIDELFQDR (SEQ ID NO: 35)
EIQNAVNGVK (SEQ ID NO: 36)
COL12A1
NVQVYDPTPNSLDVR (SEQ ID NO:
ITEVTSEGFR (SEQ ID NO: 38)
37)
VQISLVQYSR (SEQ ID NO: 39)
VYDPSTSTLNVR (SEQ ID NO: 40)
CPN2
AFGSNPDLTK (SEQ ID NO: 41)
LELLSLSK (SEQ ID NO: 42)
VCAN
VVAEDITQTSR (SEQ ID NO: 43)
LLASDAGLYR (SEQ ID NO: 44)
TDGQVSGEAIK (SEQ ID NO: 45)
ERBB3
NLDVTSLGFR (SEQ ID NO: 46)
LAEVPDLLEK (SEQ ID NO: 47)
F5
TWDQSIALR (SEQ ID NO: 48)
ASEFLGYWEPR (SEQ ID NO: 49)
F11
LSSDGSPTK (SEQ ID NO: 50)
VVSGFSLK (SEQ ID NO: 51)
FSTL1
GSDYSEILDK (SEQ ID NO: 52)
LSFQEFLK (SEQ ID NO: 53)
GNS
YYDYTLSINGK (SEQ ID NO: 54)
AFQNVFAPR (SEQ ID NO: 55)
GPR126
SLSSSSIGSDSTYLTSK (SEQ ID NO:
ISVVIQNILR (SEQ ID NO: 57)
56)
VILPQTSDAYQVSVAK (SEQ ID NO: 58)
SERPIND1
DFVDASSK (SEQ ID NO: 59)
EYYFAEAQIADFSDPAFISK (SEQ ID NO: 60)
NYNLVESLK (SEQ ID NO: 61)
SVNDLYIQK (SEQ ID NO: 62)
TLEAQLTPR (SEQ ID NO: 63)
HYOU1
VFGSQDLTTVK (SEQ ID NO: 64)
DEPGEQVELK (SEQ ID NO: 66)
VIDETWAWK (SEQ ID NO: 65)
ITGA2
YFFDVSDEAALLEK (SEQ ID NO: 67)
FGIAVLGYLNR (SEQ ID NO: 68)
ITGA3
DITIVTGAPR (SEQ ID NO: 69)
TVEDVGSPLK (SEQ ID NO: 70)
ITGA6
LWDSTFLEEYSK (SEQ ID NO: 71)
LPNAGTQVR (SEQ ID NO: 72)
ITGAM
EFDVTVTVR (SEQ ID NO: 73)
ILVVITDGEK (SEQ ID NO: 74)
ITGB2
LTDNSNQFQTEVGK (SEQ ID NO: 75)
ALNEITESGR (SEQ ID NO: 76)
KLKB1
GVNFDVSK (SEQ ID NO: 77)
DSVTGTLPK (SEQ ID NO: 78)
IAYGTQGSSGYSLR (SEQ ID NO: 79)
YSPGGTPTAIK (SEQ ID NO: 80)
KTN1
TEDSSLTK (SEQ ID NO: 81)
LQTLVSEQPNK (SEQ ID NO: 82)
LAMP2
VQPFDVTQGK (SEQ ID NO: 83)
GILTVDELLAIR (SEQ ID NO: 84)
LGALS3BP
ALGFEDATQALGR (SEQ ID NO: 85)
ELSEALGQIFDSQR (SEQ ID NO: 86)
SDLAVPSELALLK (SEQ ID NO: 87)
YSSDYFQAPSDYR (SEQ ID NO: 88)
PLXNA1
YDYTEDPTILR (SEQ ID NO: 89)
LSLPWLLNK (SEQ ID NO: 90)
POSTN
EVDDTLLVNELK (SEQ ID NO: 91)
IIDGVPVEITEK (SEQ ID NO: 92)
PTK7
SADASFNIK (SEQ ID NO: 93)
SSLQPITTLGK (SEQ ID NO: 94)
ROBO4
DLSQSPGAVPQALVAWR (SEQ ID
GPDSNVLLLR (SEQ ID NO: 96)
NO: 95)
TNC
LLETVEYDISGAER (SEQ ID NO: 97)
APTAQVESFR (SEQ ID NO: 98)
VTN
DGSLFAFR (SEQ ID NO: 99)
DVWGIEGPIDAAFTR (SEQ ID NO: 100)
FEDGVLDPDYPR (SEQ ID NO: 101)
For the quantification of de-glycosylated and non-glycosylation peptides and the ratio therebetween (the de-glycosylated/non-glycosylation peptide), it is preferred to employ a sensitive process particularly in normal and cancer samples or sample suspected of cancer. For this, abundant proteins which represent about 90% of plasma proteins such as albumin, 1 gG, 1 gA, Transferrin, Haptoglobin), Fibrinogen are removed. Or the proteins may be purified and concentrated using acetone precipitation or MWCO (molecular weight cut-off) methods to remove salts. In one embodiment of the present disclosure, the de-glycosylated peptide fragment in the N-linked glycosylation motif, NxS/T or NxC, is AsnXxxSer (SEQ ID NO: 3)/Thr or AsnXxxSer (SEQ ID NO: 3)/Cys in which asparagine in the motif is changed to aspartic acid by glycosylation. That is, the peptide fragments which are detected as a result of de-glycosylation in N-linked glycosylation motif are AspXxxSer (SEQ ID NO: 6)/Thr or AspXxxSer (SEQ ID NO: 6)/Cys.
In one embodiment of the present disclosure, a mass spectrometry is used for detecting the present markers, wherein the proteins are extracted from the appropriate samples and analyzed using the method such as described in the Examples of the present disclosure, or the literatures Kim, et al. 2010 J Proteome Res. 9: 689-99; Anderson, L et al. 2006. Mol Cell Proteomics 5: 573-88 may also be referred. In one embodiment Multiple Reaction Monitoring (MRM) technology utilizing Triple Quadrupole LC-MS/MS and QTRAP and the like may be used. MRM is a method for exactly quantifying multiple markers present in biological samples in minute amount. In MRM, by a first mass filter (Q1), parent or precursor ions are selected from the ion fragments generated in ionization source and transferred to a collision cell. And then the precursor ions arrived at the collision cell collide with internal collision gas, and are fragmented into products or daughter ions and transferred to a second mass filter (Q2), from which only the specific ions are delivered to a detector. In this way only the information of the desired target can be obtained with high selectivity and sensitivity. The literature Gillette et al., 2013, Nature Methods 10:28-34 and the like may be referred.
In other embodiment, liquid chromatography mass spectrometry is used. For example, Selected Ion Monitoring (SIM) or MRM is used, in which the peptides are not labelled and the data generated are analyzed based on the accurate MW of the peptides or proteins and the retention time of the peptides separated from the chromatography. In one embodiment, MRM is employed. In MRM analysis, peptide/transitions are monitored for analysis.
In MRM, a relative analysis without the use of labelling, or an absolute analysis using stable isotope labeled peptide standard which is injected before the analysis are used. Also for a more efficient quantification using multiple reaction monitoring, the database and programs such as TIQAM (targeted identification for quantitative analysis by MRM) may also be employed to select a unique peptide only detected in the candidate proteins and to generate and confirm MRM transition of the peptide (Anderson L, et al., Mol. Cell Proteomics. 2006, 5: 573-588).
In one embodiment, blood is obtained from a patient having a disease or suspected of a disease, which is then analyzed by LC/MS (Liquid Chromatography/Mass Spectrometer) to detect the glycosylation and de-glycosylation levels and the ratio therebetween in the appropriate proteins. The levels and/or ratios determined in the test samples are then compared to that of a control to diagnose and/or for prognosis.
As a way of example, cutoff value of a particular peptide at issue in the normal sample (upper or lower limit depending on increasing or decreasing, respectively) is determined. Then the ratio of de-glycosylation/non-glycosylation level determined in the samples from a patient having a disease or suspected of a disease is changed, i.e., decreased or increased, compared to the cutoff value, the patient is diagnosed to have a disease. The extent of increase or decrease compared to the control and the diagnosis based thereon may vary depending on the factors such as types of disease, disease properties, and types of the sample, sex and age of the patients, analysis methods and/or device. One of ordinary skill in the art would be able to select appropriate ranges or values for the diagnosis. Also the measured values may be monitored for its recovery to a normal level to follow up a therapeutic efficacy of the treatment. The present methods may be used alone or in combination with a conventional method.
In the present methods, de-glycosylation and non-glycosylation of multiple proteins in one sample may be detected simultaneously or individually. For example a maximum of about 1,000 peptides including de-glycosylated and non-glycosylated peptides may be detected at one time, this represents the detection of about 500 glycosylated proteins. When the multiple proteins are analyzed for a particular disease, the data from the analysis are combined and used to create a panel specialized for a particular disease, which increases the accuracy (specificity and sensitivity) of the diagnosis of a disease such as cancer.
In other aspect, the present methods may be used for screening the cancer marker by detecting the various glycoproteins glycosylated and/or de-glycosylated in a particular cancer, which may be more sensitive and specific compared to a conventional marker.
The term biomarker for diagnosing or diagnosis marker as used herein refers to an agent that may discriminate a cancer tissues or cells from normal cells or a treated cancer tissues or cells, and comprises an organic and biological molecule and the like, such as proteins or nucleic acid molecules, lipid, glycolipid, and glycoprotein that has increased or decreased in tissues or cells compared with normal control samples. In the present disclosure, as markers for a hepatocellular cancer, glycoproteins the expression level or the extent of glycosylation of which are decreased or increased are employed and include AFP, Alpha-2-antiplasmin (SERPINF2), Alpha-2-macroglobulin (A2M), Apolipoprotein B-100 (APOB), Beta-galactosidase (GLB1), Bone morphogenetic protein 1 (BMP1), Corticosteroid-binding globulin (SERPINA6), Complement factor H (CFH), Cholinesterase (BCHE), Clusterin (CLU), Collagen alpha-1(XII) chain (COL12A1), Carboxypeptidase N subunit 2 (CPN2), Versican core protein (VCAN), Receptor tyrosine-protein kinase erbB-3 (ERBB3), Coagulation factor V (F5), Coagulation factor XI (F11), Alpha-fetoprotein (AFP), Follistatin-related protein 1 (FSTL1), N-acetylglucosamine-6-sulfatase (GNS), G-protein coupled receptor 126 (GPR126), Heparin cofactor 2 (SERPIND1), Hypoxia up-regulated protein 1 (HYOU1), Integrin alpha-2 (ITGA2), Integrin alpha-3 (ITGA3), Integrin alpha-6 (ITGA6), Integrin alpha-M (ITGAM), Integrin beta-2 (ITGB2), Plasma kallikrein (KLKB1), Kinectin (KTN1), Lysosome-associated membrane glycoprotein 2 (LAMP2), Galectin-3-binding protein (LGALS3BP), Plexin-A1 (PLXNA1), Periostin (POSTN), Inactive tyrosine-protein kinase 7 (PTK7), Roundabout homolog 4 (ROBO4), Tenascin (TNC), Vitronectin (VTN).
In the present disclosure, the present markers may be used in alone or two or more markers may be used in combination to further improve the specificity and/or sensitivity. For example, two, three, four, five, six, seven or more markers may be combined. The person skilled in the art would be able to select the combination of markers that show a desired sensitivity and specificity using the methods such as Logistic regression analysis and/or analysis of the biological samples from the subjects including a normal person and patient using the methods such as described in the examples of the present disclosure.
In other aspect, the present disclosure relates to a method for screening a maker for cancer diagnosis. According to one embodiment, the method comprises steps of providing a protein(s) containing N-linked glycosylation motifs wherein the proteins are glycosylated at all or part of the motif, and the proteins are from a normal control sample and a cancer sample; de-glycosylating the proteins in the sample; fragmenting the de-glycosylated proteins; determining in the fragmented proteins the amount of the de-glycosylated peptide at the N-linked motif and the amount of the non-glycosylated peptide which does not contain the N-linked motif and the ratio therebetween; and selecting the protein as a marker if the ratio is changed in the sample compared to that of a control.
The elements recited in the methods are as described hereinbefore.
The proteins having N-linked glycosylation motif comprise glycoproteins are from a sample such as cancer tissues, cells or from bodily fluids such as blood or from a normal sample or from sample of a cured cancer patient, and the level and/or extent of which change, i.e., are increased or decreased compared to a control sample. These glycoproteins may be screened from the glycoproteins known in the art.
In other aspect, the present disclosure relates to a kit which is used for the present methods. The kit comprises an enzyme(s) for de-glycosylating the proteins or sample comprising NxST motif, an enzyme(s) for fragmenting the proteins and agents for quantifying the de-glycosylated fragments or peptide and the non-glycosylated fragment or peptide. The elements recited in the present kits are as described hereinbefore.
The present disclosure is further explained in more detail with reference to the following examples. These examples, however, should not be interpreted as limiting the scope of the present invention in any manner.
The following experiments was performed using a standard protein to confirm the possibility of discovering or developing markers based on the quantification of glycosylated peptides and de-glycosylated peptides using MRM technology and its use in diagnostics.
As shown in
Among the commercially available proteins which are purified and lyophilized, a protein in which both the glycosylated peptide having NxS/T motif and the non-glycosylated peptide without the motif are selected as predictable transitions in Skyline has been used as a standard.
In the present example, Invertase-1protein was used as a standard and the sequence is as shown in
The native form of the sequence of the standard protein and the conversion form thereof in which N is changed to D at NxS/T motif were imported into Skyline (https://brendanx-uw1.gs.washington.edu/labkey/project/home/software/Skyline/begin.view) program to select a theoretical transition value. At the same time, synthetic peptides with the same sequence except that 12C and 14N atoms in Arg (R) and Lys (K) residues at the C-terminal region were heavy labelled with 13C and 15N were used to confirm that the peptides detected are actually from the peptides of interest to be detected.
That is, the heavy labelled peptide and the endogenous peptide share the same sequence and have the identical hydrophobicity. Thus they can be detected on LC-column (C18) since they are eluted at the same retention time.
As a result of the selection, Q1 difference of 0.49 Da and Q3 difference of 0.98 Da between the native and conversion sequence have been found. The difference between the endogenous peptide and the heavy labelled peptide were found to be 4.00 Da (5.00 Da) in Q1 and 8.01 Da (10.01 Da) in Q3. The transition analysis results are as below in Table 2.
TABLE 2
Native_sequence
Conversion_sequence
Peptide
Ion
Precursor
Product
Peptide
Precursor
Product
sequence
Isotype
Name
Ion (Q1)
Ion (Q2)
sequence
Isotype
Ion Name
Ion (Q1)
Ion (Q2)
NPVLAAASTQFR
light
y9
699.349125
10077.526869
NPVLAADSTQFR
light
y9
659.841133
1008.510885
(SEQ ID NO:
light
y8
699.349125
894.442805
(SEQ ID NO:
light
y8
699.841133
899.426821
104)
light
y7
699.349125
823.405691
105)
light
y7
659.841133
824.382707
light
y6
699.349125
752.368578
light
y6
699.841133
753.352593
light
y5
699.349125
638.32565
light
y5
659.841133
638.32565
NPVLAAASTQFR
heavy
y9
664.35326
1017.535138
NPVLAADSTQFR
heavy
y9
664.845268
1018.519154
(SEQ ID NO:
heavy
y8
664.35326
904.453074
(SEQ ID NO:
heavy
y8
664.845268
905.43903
104)
heavy
y7
664.35326
833.41396
105)
heavy
y7
664.845268
834.397976
heavy
y6
664.35326
762.376847
heavy
y6
664.845268
763.360862
heavy
y5
664.35326
628.333919
heavy
y5
664.845268
648.333919
IEIYSSDDLK
light
y9
591.798068
1069.904798
IEIYSSDDLK
light
y9
591.798068
1069.504796
(SEQ ID NO:
light
y8
591.798068
941.462203
(SEQ ID NO:
light
y8
591.798068
941.462203
108)
light
y7
591.799068
827.378139
108)
light
y7
591.798068
827.378139
light
y6
591.799068
664.314811
light
y6
591.798068
664.314811
light
b3
591.798068
356.217997
light
b3
591.798068
356.217997
IEIYSSDDLK
heavy
y9
595.995168
1077.518995
IEIYSSDDLK
heavy
y9
595.805168
1077.518995
(SEQ ID NO:
heavy
y8
595.805168
948.476402
(SEQ ID NO:
heavy
y8
595.905168
948.876422
108)
heavy
y7
595.805168
835.792328
108)
heavy
y7
595.805168
835.392338
heavy
y6
595.805168
672.32901
heavy
y6
595.805168
672.32901
heavy
b3
595.805168
355.217997
heavy
b3
595.805168
356.217997
VVDFGK
light
y5
332.686864
565.298038
WDFGK
light
y5
332.686854
565.299038
(SEQ ID NO:
light
y4
322.686864
466.229624
(SEQ ID NO:
light
y4
332.686854
466.243823
109)
light
y3
322.686864
351.302681
109)
light
y3
332.686854
351.202681
light
y2
322.686864
204.134257
light
y2
332.686854
204.134267
light
b2
332.686864
199.144104
light
b2
332.686854
199.144104
VVDFGK
heavy
y5
336.699964
573.312237
VVDFGK
heavy
y5
336.693364
573.312237
(SEQ ID NO:
heavy
y4
336.699964
474.243823
(SEQ ID NO:
heavy
y4
336.693364
474.243823
109)
heavy
y3
336.699964
393.21589
109)
heavy
y3
336.693964
399.21688
heavy
y2
336.699964
212.3484688
heavy
y2
336.693964
212.148666
heavy
b2
336.699964
199.144104
heavy
b2
338.693964
199.144104
FATDTTLTK
light
y8
498.771657
849.467623
FATDTTLTK
light
y8
499.263664
890.451639
(SEQ ID NO:
light
y7
498.771657
778.430509
(SEQ ID NO:
light
y7
499.263664
779.414525
106)
light
y6
498.771657
677.382831
107)
light
y6
499.263664
678.366845
light
y5
498.771657
593.339903
light
y5
499.263664
563.339903
light
y4
498.771657
462.292225
light
y4
499.263664
462.292225
FATATTLTK
heavy
y8
502.778756
857.481822
FATATTLTK
heavy
y8
503.270764
858.465838
(SEQ ID NO:
heavy
y7
502.778756
785.444708
(SEQ ID NO:
heavy
y7
503.270764
787.428724
106)
heavy
y6
502.778756
655.39703
107)
heavy
y6
503.270764
686.381045
heavy
y5
502.778756
571.354102
heavy
y5
503.270764
571.354102
heavy
y4
502.778756
470.306424
heavy
y4
503.270764
470.306424
Hundred μg of standard protein was treated with urea and DTT at the final concentration of 6M urea/20 mM DTT (dithiothreitol) in Tris pH 8.0 and reduced at 37° C. for 60 min. Then the product was alkylated with IAA (iodoacetamide) at the final concentration of 50 mM at RT for 30 min. Then the product was diluted with 100 mM Tris pH 8.0 to bring the concentration of Urea not more than 0.6M. Then the de-glycosylated peptides were treated with 2 μl (500,000 units/ml) of PNGase-F (Peptide N Glycosidase) (NEW ENGLAND BioLabs Inc. P0704L) and incubated at 37° C. for 16 hrs, which were then treated with trypsin at a ratio of 1:50 (w/w) trypsin to peptides and incubated at 37° C. for 12 hrs. Then the resulting products were treated with a formic acid solution at the final concentration of 5%. And as a control the glycosylated peptides was treated with 2 μl of water under the same condition. Then desalting reaction was performed as follows using OASIS cartridge (Waters, USA) as suggested by the manufacturer's instruction. The desalted peptides were dissolved in Sol A buffer (97% D.W, 3% ACN, 0.1% formic acid) followed by a centrifugation at 15,000 rpm for 60 min, and then used for MRM analysis.
To confirm the possibility of the quantification, experiments to confirm the linearity of the heavy labelled synthetic peptide to the target peptide as follows. For this, a serious dilution of 0, 4, 13, 40, 120, 370 fmol of the heavy labelled synthetic peptide was prepared, to which a 370 nmol of the target peptide corresponding to the standard glycosylated protein was added for the analysis. For the glycosylated standard glycoprotein sample, heavy labelled synthetic peptide of N-form having Asn residue was used. For the de-glycosylated standard glycoprotein sample, heavy labelled synthetic peptide of D-form having Asp residue was used. All the experiments were repeated 3 times.
Liquid chromatography (LC) 1260 capillary LC system from Agilent was used. For the peptide separation, Capillary RR 0.3×150, 3.5 μm (Cat.N 5064-8261) was used. Five microliter of peptide sample was directly injected into the column without passing through a trap column and eluted at a flow rate of 20 L/min,
Column was equilibrated with SolA (97% Distilled Water, 3% acetonitrile, 0.1% formic acid) for 10 min and eluted with SolB (3% Distilled Water, 97% acetonitrile, 0.1% formic acid) in 45 min and then on a linear gradient of 5% to 60% and of 85% in 5 min.
Mass spectrometry 6490-Triple quadrupole (QQQ) from Agilent technology was used to monitor the transition of the selected protein under MRM mode. The settings were as follows: gas temperature of 200° C., gas flow of 14 L/min, nebulizer at 20 psi, sheath gas temperature of 250° C. and sheath gas flow of 11 L/min. The voltage applied for the capillary and nozzle was 3000V.
The unit resolution of 0.7 Da was used for Quadruple 1(Q1) and Quadruple 3 (Q3). The dwell time was set to 2 sec for a total cycle in an unscheduled MRM mode. Then the retention time was selected after the analysis for all the target peptides were completed, based on which the analysis were repeated 3 times at the window size 3 min.
The results of MRM analysis for the standard glycoprotein are shown in
Results of the analysis performed on NPVLAANSTQFR (SEQ ID NO: 104) (the glycosylated peptide 1)/FATNTTLTK (SEQ ID NO: 106) (the glycosylated peptide 2) are shown in
TABLE 3-1
NPVLAANSTQFR (SEQ ID NO: 104)_endo_Buffer
Heavy
Peak area
Endo
Peak area
conc.
CV
conc.
CV
(fmol)
Average
STDEV
(%)
(nmol)
Average
STDEV
(%)
0.0
0.0
0.0
0.0
370.0
0.0
0.0
0.0
4.0
567.0
140.5
24.8
370.0
0.0
0.0
0.0
13.0
1803.0
439.7
24.4
370.0
0.0
0.0
0.0
40.0
6312.7
985.4
15.6
370.0
0.0
0.0
0.0
120.0
19215.0
2691.7
14.0
370.0
0.0
0.0
0.0
370.0
71184.7
2395.1
3.4
370.0
0.0
0.0
0.0
TABLE 3-2
NPVLAADSTQFR (SEQ ID NO: 105)_heavy_PNGase-F
Heavy
Peak area
Endo
Peak area
conc.
CV
conc.
CV
(fmol)
Average
STDEV
(%)
(nmol)
Average
STDEV
(%)
0
0.0
0.0
0.0
370.0
6543.0
535.2
8.2
4
0.0
0.0
0.0
370.0
8770.7
1578.1
18.0
13
2745.0
992.7
36.2
370.0
8679.7
1077.0
12.4
40
9385.0
1541.2
16.4
370.0
8590.7
921.5
10.7
120
32455.0
757.8
2.3
370.0
8466.7
546.7
6.5
370
125243.3
4397.1
3.5
370.0
8050.0
1124.4
14.0
TABLE 4-1
FATNTTLTK (SEQ ID NO: 106)_endo_Buffer
Heavy
Peak area
Endo
Peak area
conc.
CV
conc.
CV
(fmol)
Average
STDEV
(%)
(nmol)
Average
STDEV
(%)
0.0
0.0
0.0
0.0
370.0
0.0
0.0
0.0
4.0
3251.7
377.5
11.6
370.0
0.0
0.0
0.0
13.0
8573.7
828.6
9.7
370.0
0.0
0.0
0.0
40.0
29945.7
2731.4
9.1
370.0
0.0
0.0
0.0
120.0
90011.0
8249.9
9.2
370.0
0.0
0.0
0.0
370.0
347197.7
38220.6
11.0
370.0
0.0
0.0
0.0
TABLE 4-2
FATDTTLTK (SEQ ID NO: 107)_heavy_PNGase-F
Heavy conc.
Peak area
Endo conc.
Peak area
(fmol)
Average
STDEV
CV (%)
(nmol)
Average
STDEV
CV (%)
0
0.0
0.0
0.0
370.0
211051.0
11726.5
5.6
4
5316.0
329.5
6.2
370.0
221477.7
10614.3
4.8
13
15605.3
1789.6
11.5
370.0
224643.3
3350.8
1.5
40
51313.7
3243.6
6.3
370.0
231082.7
12938.0
5.6
120
178115.7
6992.8
3.9
370.0
212931.0
19169.8
9.0
370
585547.3
24593.9
4.2
370.0
221705.7
19232.9
8.7
Results of the analysis performed on the non-glycosylated peptides IEIYSSDDLK (SEQ ID NO: 108)/VVDFGK (SEQ ID NO: 109) are shown in
When the serially diluted heavy labelled peptide was added to the de-glycosylated and the glycosylated samples, the endogenous peptide from the standard glycoprotein and the heavy labelled peptide were co-eluted at the identical time. Also the strength of five product ion type was confirmed to be identical. The linearity of the heavy labelled synthetic peptide was confirmed to be R^2=0.9993, 0.9994/R^2=0.9981, 0.9997. Further the endogenous peptides were found to have a strength that is lower than the de-glycosylated sample treated with PNGase-F.
TABLE 5-1
VVDFGK (SEQ ID NO: 109)_heavy_PNGase-F
Heavy conc.
Peak area
Endo conc.
Peak area
(fmol)
Average
STDEV
CV (%)
(nmol)
Average
STDEV
CV (%)
0
0.0
0.0
0.0
370.0
108440.0
6087.6
5.6
4
8115.3
419.8
5.2
370.0
117271.7
3679.3
3.1
13
28533.7
1532.7
5.4
370.0
105682.0
5422.9
5.1
40
81770.0
3646.6
4.5
370.0
118207.0
4490.0
3.8
120
312418.0
7315.0
2.3
370.0
113168.7
466.2
0.4
370
930225.7
11860.0
1.3
370.0
113721.0
7408.0
6.5
TABLE 5-2
IEIYSSDDLK (SEQ ID NO: 107)_endo_Buffer
Heavy conc.
Peak area
Endo conc.
Peak area
(fmol)
Average
STDEV
CV (%)
(nmol)
Average
STDEV
CV (%)
0.0
0.0
0.0
0.0
370.0
16515.0
907.5
5.5
4.0
1265.7
405.5
32.0
370.0
20640.7
1143.2
5.5
13.0
3385.3
302.5
8.9
370.0
17470.3
2239.6
12.8
40.0
10699.0
2104.3
19.7
370.0
21598.0
910.4
4.2
120.0
42808.7
3793.7
8.9
370.0
20738.0
1253.4
6.0
370.0
148574.0
2126.4
1.4
370.0
23795.3
838.5
3.5
TABLE 6-1
IEIYSSDDLK (SEQ ID NO: 108)_heavy_PNGase-F
Heavy
Peak area
Endo
Peak area
conc.
CV
conc.
CV
(fmol)
Average
STDEV
(%)
(nmol)
Average
STDEV
(%)
0
0.0
0.0
0.0
370.0
22047.3
342.0
1.6
4
1457.0
534.5
36.7
370.0
27167.3
1216.9
4.5
13
4585.0
237.8
5.2
370.0
26529.3
3219.1
12.1
40
15154.0
1538.5
10.2
370.0
30355.7
1660.5
5.5
120
56990.0
3247.2
5.7
370.0
25508.3
1855.0
7.3
370
186285.0
10110.8
5.4
370.0
29249.3
2171.6
7.4
TABLE 6-2
VVDFGK (SEQ ID NO: 109)_heavy_PNGase-F
Heavy conc.
Peak area
Endo conc.
Peak area
(fmol)
Average
STDEV
CV (%)
(nmol)
Average
STDEV
CV (%)
0
0.0
0.0
0.0
370.0
108440.0
6087.6
5.6
4
8115.3
419.8
5.2
370.0
117271.7
3679.3
3.1
13
28533.7
1532.7
5.4
370.0
105682.0
5422.9
5.1
40
81770.0
3646.6
4.5
370.0
118207.0
4490.0
3.8
120
312418.0
7315.0
2.3
370.0
113168.7
466.2
0.4
370
930225.7
11860.0
1.3
370.0
113721.0
7408.0
6.5
Summarizing the results of the experiments using the standard glycoprotein, the de-glycosylated peptide in D-form was detected in MRM analysis as shown in
The institutional review board of Seoul National University Hospital approved the protocol of the present invention, and the written informed consent was obtained from each patient or their legally authorized representative. The clinical characteristics of the patients are as in Table 7.
In the present examples, 60 normal and 60 liver cancer samples were used. The samples were selected to include more sample from men than women in consideration of the higher ratio of liver cancer found in men than women. Although liver cancers are classified into virus origin (HBV, HCV) and alcoholic origin, only the liver cancer samples of HBV origin were selected in consideration of the fact that HBV is the highest cause of liver cancer in Asia and Africa.
TABLE 7
MRM analysis
HCC Group
Healthy group
Total patient number
60
60
Gender (Male/Female)
42/18
41/19
Age (Mean, Range)
58 (38-76)
53 (32-74)
Etiology of liver disease
HBV, 60 (100%)
Locoregional modality
TACE
30
PEIT
22
TACE & PEIT
4
RFA
3
Operation
1
APP value (Mean, Range)
12174 (3-283000)
<20 ng/ml
26
20-200 ng/ml
11
200-1000 ng/ml
11
>1000 ng/ml
12
PIVKA value (Mean, Range)*
993 (3-13641)
<40 ng/ml
26
40-400 ng/ml
13
400-1000 ng/ml
5
>1000 ng/ml
13
*PIVKA values were provided for 58(M40F18) among a total of 60 HCC group
Abbreviations
AFP: Alpha-Fetoprotein
PIVKA: Proteins induced by vitamin K absence or antagonist
TACE: Transcatheter arterial chemoembolition
PEIT: Percutanious ethanol injection therapy
RFA: Radiofrequency ablation
In case of alpha-fetoprotein (AFP) known as a biomarker for liver cancer, the peptide sequence in which the NxS/T motif is glycosylated is VNFTEIQ (SEQ ID NO: 9). The glycosylated peptide comprising NxS/T motif and the non-glycosylated peptide without the motif were analyzed using Skyline program to determine the possible transition (refer to Example 2-3). The sequence of the full-length is shown in
To further discover the potential glycosylated protein markers specific for liver cancer, 495 glycosylated proteins which contain NxS/T motif(s) and are known to be N-glycosylated at the motif were selected from Plasma Proteome Database (PPD). The transition was determined using Skyline program for the peptides containing the motif and being glycosylated and for the non-glycosylated peptide without the motif. Through this process, a total of 406 proteins, 1637 peptides, and 9821 transitions (Q1/Q3) were selected for the non-glycosylated peptides. For the glycosylated peptides, a total of 240 proteins, 363 peptides, and 4111 transitions (Q1/Q3) were selected.
As described in Example 1 for the analysis of standard protein, AFP protein in a native form and conversion form in which N is substituted with D was imported into Skyline program to determine the theoretical transition (in silico prediction). As a result, Q1 and Q3 differences between the two types of peptides were found to be 0.49 Da and 0.98 Da, respectively. Results are shown in Table 8. Other proteins in Example 2-2 from liver cancer were analyzed in the same way.
TABLE 8
Native sequence
Peptide
Precursor
Product
sequence
Isotype
Ion name
Ion (Q1)
Ion (Q3)
VNFTEIQK
light
y7
489.766374
879.457058
(SEQ ID
light
y6
489.766374
765.414131
NO: 9)
light
y5
489.766374
618.345717
light
y4
489.766374
517.298038
light
y2
489.766374
275.171381
GYQELLEK
light
y6
490.258382
759.424696
(SEQ ID
light
y5
490.258382
631.366118
NO: 10)
light
y3
490.258382
389.239461
light
b2
490.258382
221.092068
light
b6
490.258382
704.361367
VDFTEIQK
light
y7
490.258382
880.441074
(SEQ ID
light
y6
490.258382
765.414131
NO: 9)
light
y5
490.258382
618.345717
light
y4
490.258382
517.298038
light
y2
490.258382
275.171381
GYQELLEK
light
y6
490.258382
759.424696
(SEQ ID
light
y5
490.258382
631.366118
NO: 10)
light
y3
490.258382
389.239461
light
b2
490.258382
221.092068
light
b6
490.258382
704.361367
Each of sixty normal control and HCC patient samples were pooled into three groups by twenty samples. Major six proteins in serum (albumin, 1 gG, 1 gA, transferrin, haptoglobin, alpha-1-antitrypsin) were removed using MARS (Part #5185-5984, multiple affinity removal system, Agilent Technologies, USA) according to the manufacturer's instruction.
Then the serum proteins were concentrated using a filter (3K Amicon, USA) and quantified using BCA (bicinchoninic acid (BCA) assay, Sigma-Aldrich, USA) kit according to the manufacturer's instruction. Then 100 μg of the protein was treated either with water (control) or PNGase-F followed by treatment with trypsin to de-glycosylate the protein.
For quality control of the data obtained and the stability confirmation of the instrument, peptides in which C and N atoms of arginines are heavy labelled were used as an internal standard. The peptide sequence used is LNVENPK from E. coli and thus not present in human serum, which was used at the concentration of 5 fmol per analysis.
Experiments were repeated 3 times per group and then the data obtained were imported into Skyline and converted into the transition area for each peptide. Then the peak area obtained from the AFP target peptide were normalized by the peak area obtained from the heavy labelled internal standard.
Results from the experiments in which the control glycosylated sample treated only with water (control) and the de-glycosylated sample treated with PNGase-F were analyzed for VNFTEIQK (VDFTEIQK (SEQ ID NO: 9)) peptides are shown in
In contrast, with HCC samples, when N-form VNFTEIQK (VDFTEIQK (SEQ ID NO: 9)) was used for the glycosylated samples and D-form VDFTEIQK (SEQ ID NO: 9) was used for the de-glycosylated samples, the de-glycosylated samples analyzed for D-form were only detected.
This is due to the fact that the expression level of AFP is increased in HCC samples compared to the control and thus comes within the level to be detected by Mass spectrometry in contrast to the glycosylated samples in which case the mass of the peptide is changed due to the glycosylation and thus the peptide is not detected and only the de-glycosylated samples are detected.
Results from the experiments in which the control glycosylated sample treated only with water (control) and the de-glycosylated sample treated with PNGase-F were analyzed for the non-glycosylated GYQELLEK (SEQ ID NO: 10) peptide are shown in
In summary, when the serum from the pooled normal control sample and HCC sample were treated with PNGase-F/trypsin and the de-glycosylated samples were analyzed for the de-glycosylated peptide VDFTEIQK (SEQ ID NO: 9) and the non-glycosylated peptide GYQELLEK (SEQ ID NO: 10), a 27.3 fold difference was found between HCC group and the normal group when analyzed for VDFTEIQK (SEQ ID NO: 9) in comparison to a 5.3 fold difference when analyzed for GYQELLEK (SEQ ID NO: 10) as shown in Tables 9 and 10, and
TABLE 9
Normal group
Cancer group
Set
Average
STDEV
CV (%)
Average
STDEV
CV (%)
1
0.0011
0.0004
38.5054
0.0731
0.0054
7.3393
2
0.0030
0.0012
40.6544
0.0124
0.0011
8.9907
3
0.0015
0.0015
104.7847
0.0652
0.0076
11.7206
TABLE 10
Normal group
Cancer group
Set
Average
STDEV
CV (%)
Average
STDEV
CV (%)
1
0.0158
0.0035
22.3136
0.1020
0.0051
5.0402
2
0.0129
0.0065
50.2251
0.0077
0.0034
44.6222
3
0.0093
0.0031
32.9208
0.0907
0.0037
4.0869
In addition to AFP, further analysis have been done to further discover the candidates of glycosylated protein markers, as a result, a total of 354 proteins and 1000 peptides therefrom were detected in the liver cancer in comparison to the normal sample. From them, 145 proteins as glycoproteins with NxS/T motif, and 182 peptides therefrom as the de-glycosylated peptide after being treated with PNGase-F were determined. The de-glycosylated peptides and glycosylated peptides used for the detection are listed in Table 16.
The preparation and MRM analysis of the individual samples from 60 normal samples and 60 HCC samples were prepared as described in Example 2.
For normalization, the synthetic heavy labelled peptide for the de-glycosylated peptide and the non-glycosylated peptide were used at the concentration of 7.3 fmol and 10.3 fmol, respectively.
All the individual samples were analyzed once and the data were imported into Skyline and converted into the area of the peptide transition. The peak area to AFP target peptide was normalized to the peak area value of the corresponding heavy labelled synthetic peptide.
In addition to AFP, the peptides or proteins which have shown at least 3 times signal to noise (S/N) ratio in the pooled clinical sample and which have been confirmed to flow in at least 3 product ions at the same retention time.
The present Example was performed to optimize the collision energy to improve the degree of detection.
As a result of selecting the transition (Q1/Q3) of the target peptide, the difference between the endogenous peptide and the heavy labelled peptide difference was found to be 4.00 Da (5.00 Da) for Q1 and 8.01 Da (10.01 Da) for Q3.
To determine the optimized collision energy (CE) for the heavy labelled synthetic peptide of AFP, a total of 11 points of CE including 2 units before and after the default CE value were analyzed for 3 times and the CE with the highest peak area was confirmed. The results are shown in
TABLE 11
Peptide
Precursor ion
Product ion
Optimized collision
Protein name
sequence
Isotype
(m/z)
(m/z)
energy (volt)
Ion type
Alpha-fetoprotein
VOFTEIQK
light
490.258382
880.441074
13.3
y7
(AFP)
(SEQ ID
light
490.258382
765.414131
13.3
y6
NO: 9)
light
490.258382
618.345717
15.3
y5
light
490.258382
517.298038
11.3
y4
light
490.258382
388.255445
21.3
y3
light
490.258382
275.171381
21.3
y2
light
490.258382
362.171047
9.3
b3
light
490.258382
463.218725
9.3
b4
light
490.258382
592.261319
11.3
b5
light
490.258382
705.345383
9.3
b6
light
490.258382
833.40396
7.3
b7
VDFTEIQK
heavy
494.265481
888.455273
13.3
y7
(SEQ ID
heavy
494.265481
773.42833
13.3
y6
NO: 9)
heavy
494.265481
626.359916
15.3
y5
heavy
494.265481
525.312237
11.3
y4
heavy
494.265481
396.269644
21.3
y3
heavy
494.265481
283.18558
21.3
y2
heavy
494.265481
362.171047
9.3
b3
heavy
494.265481
463.218725
9.3
b4
heavy
494.265481
592.261319
11.3
b5
heavy
494.265481
705.345383
9.3
b6
heavy
494.265481
833.40396
7.3
b7
GYQELLEK
light
490.258382
759.424636
11.3
y6
(SEQ ID
light
490.258382
631.366118
13.3
y5
NO: 10)
light
490.258382
502.323525
15.3
y4
light
490.258382
389.239461
17.3
y3
light
490.258382
276.155397
21.3
y2
light
490.258382
221.092068
11.3
b2
light
490.258382
349.150646
9.3
b3
light
430.258382
591.277303
11.3
b5
light
490.258382
704.361367
7.3
b6
light
490.258382
833.40396
9.3
b7
GYQELLEK
heavy
494.265481
767.438895
11.3
y6
(SEQ ID
heavy
494.265481
639.380317
13.3
y5
NO: 10)
heavy
494.265481
510.337724
15.3
y4
heavy
494.265481
397.25366
17.3
y3
heavy
494.265481
284.169536
21.3
y2
heavy
494.265481
221.092068
11.3
b2
heavy
494.265481
349.150646
9.3
b3
heavy
494.265481
591.277303
11.3
b5
heavy
494.265481
704.361367
7.3
b6
heavy
494.265481
833.40396
9.3
b7
Using a heavy labelled synthetic peptide with the same sequence as AFP target peptide (De-glycopeptide, Non-glycopeptide) except that 12C and 14N atoms in Arg (R) and Lys (K) residues at the C-terminal region were heavy labelled with 13C and 15N were used to confirm that the peptides detected are actually the endogenous peptide present in serum.
That is, the heavy labelled peptide and the endogenous peptide share the same sequence and thus have the identical hydrophobicity. Thus they can be detected on LC-column (C18) since they are eluted at the same retention time.
The de-glycosylated peptide VDFTEIQK (SEQ ID NO: 9) and the non-glycosylated peptide GYQELLEK (SEQ ID NO: 10) were analyzed on the de-glycosylated peptide obtained by treatment with PNGase-F/trypsin together with the heavy labelled synthetic peptide. As a result, the endogenous peptides from serum and the heavy labelled synthetic peptide were eluted at the same retention time. Also the strength of the product ion type was determined to be identical. Results are shown in
To confirm the quantifiable property of the heavy labelled synthetic peptides to AFP target peptide, experiments to confirm the linearity of the reaction curve was performed as follows. The heavy labelled synthetic peptide for the de-glycosylated peptide VDFTEIQK (SEQ ID NO: 9) was serially diluted to 0, 0.8, 1.6, 3.1, 6.3, 12.5, 25, 50, 100 fmol. The heavy labelled synthetic peptide for the non-glycosylated peptide GYQELLEK (SEQ ID NO: 10) was serially diluted to 0, 1.6, 3.1, 6.3, 12.5, 25, 50, 100, 200 fmol. Then 5 μg of serum from the pooled sample was added to each of the diluted peptides.
Experiments were repeated 3 times for each concentration. As a result, both the synthetic peptides were found to have a linearity (R^2=0.995, 0.992). Results are shown in
TABLE 12
VDFTEIQK (SEQ ID NO: 9) (494.3/773.4)_2+_y6
Conc. (fmol)
Blank
0
0.8
1.6
3.1
6.3
12.5
25
50
100
MeanArea
7.00
307.00
610.00
1109.33
1296.67
1900.33
12319.33
25216.00
61973.00
138138.00
Stdev
5.57
14.11
61.59
83.20
12.90
194.20
76.85
669.63
1838.58
3336.99
CV (%)
79.54%
4.60%
9.62%
7.50%
0.99%
10.22%
0.62%
2.66%
2.831%
2.42%
GYQELLEX (SEQ ID NO: 10) (494.3/767.4)_2+_y6
Conc. (fmol)
Blank
0.0
1.6
3.1
6.3
12.5
25.0
50.0
100.0
200.0
MeanArea
7.33
70.67
441.00
524.33
1061.33
8809.33
1686.33
48325.33
109508.67
259150.09
Stdev
2.31
48.60
9.64
28.45
121.23
277.69
809.40
1110.34
5383.50
13769.43
CV (%)
31.49%
68.78%
2.19%
5.43%
11.39%
3.15%
5.03%
2.30%
4.92%
5.31%
MRM analysis was performed on 60 normal samples as described in Example. As shown in Table 13-1 to 13-3, the de-glycosylated peptide VDFTEIQK (SEQ ID NO: 9) was detected in two samples (3.3%) out of sixty. The non-glycosylated peptide GYQELLEK (SEQ ID NO: 10) was detected in seven samples out of sixty samples (11.7%). Based on this, the specificity with which the liver cancer can be differentiated from the normal person was found to be 96.7% for the de-glycosylated peptide and 88.3% for the non-glycosylated peptide.
TABLE 13-1
Set 1
Detection
(Normal group)
N.
T. #
Test Date
Sex
Age
Deglycopeptide
Non-glycopeptide
1
N12-051
2012 Mar. 28
M
53
Not detected
Not detected
2
N12-052
2012 Mar. 23
M
43
Not detected
Not detected
3
N12-055
2012 Mar. 23
M
59
Not detected
Not detected
4
N12-057
2012 Mar. 23
M
59
Not detected
Not detected
5
N12-059
2012 Mar. 28
M
42
Not detected
Not detected
6
N12-061
2012 Mar. 23
M
61
Not detected
Detected
7
N12-062
2012 Mar. 23
M
60
Not detected
Detected
8
N12-069
2012 Mar. 23
M
47
Not detected
Not detected
9
N12-081
2012 Mar. 23
M
51
Not detected
Detected
10
N12-082
2012 Mar. 29
M
44
Not detected
Not detected
11
N12-085
2012 Mar. 26
M
42
Not detected
Not detected
12
N12-086
2012 Mar. 26
M
51
Not detected
Not detected
13
N12-088
2012 Mar. 26
M
54
Not detected
Not detected
14
N12-095
2012 Mar. 26
M
69
Not detected
Not detected
15
N12-054
2012 Mar. 28
F
66
Not detected
Not detected
16
N12-060
2012 Mar. 23
F
64
Not detected
Not detected
17
N12-075
2012 Mar. 28
F
55
Detected
Not detected
18
N12-084
2012 Mar. 26
F
53
Not detected
Not detected
19
N12-087
2012 Mar. 26
F
39
Not detected
Not detected
20
N12-108
2012 Mar. 26
F
51
Not detected
Not detected
TABLE 13-2
Set 2
Detection
(Normal group)
N.
T. #
Test Date
Sex
Age
Deglycopeptide
Non-glycopeptide
21
N12-096
2012 Mar. 26
M
48
Not detected
Not detected
22
N12-097
2012 Mar. 26
M
55
Not detected
Not detected
23
N12-101
2012 Mar. 26
M
48
Not detected
Not detected
24
N12-109
2012 Mar. 26
M
69
Not detected
Not detected
25
N12-112
2012 Mar. 26
M
70
Not detected
Not detected
26
N12-120
2012 Mar. 26
M
45
Not detected
Not detected
27
N12-122
2012 Mar. 26
M
52
Not detected
Not detected
28
N12-125
2012 Mar. 26
M
59
Not detected
Not detected
29
N12-126
2012 Mar. 26
M
47
Not detected
Not detected
30
N12-127
2012 Mar. 26
M
66
Not detected
Detected
31
N12-130
2012 Mar. 26
M
53
Not detected
Not detected
32
N12-181
2012 Mar. 26
M
43
Not detected
Not detected
33
N12-188
2012 Mar. 28
M
43
Not detected
Not detected
34
N12-199
2012 Mar. 28
M
56
Not detected
Not detected
35
N12-110
2012 Mar. 26
F
62
Not detected
Not detected
36
N12-117
2012 Mar. 26
F
49
Not detected
Not detected
37
N12-119
2012 Mar. 26
F
37
Not detected
Not detected
38
N12-128
2012 Mar. 26
F
42
Not detected
Not detected
39
N12-189
2012 Mar. 28
F
58
Not detected
Not detected
40
N12-202
2012 Mar. 28
F
65
Not detected
Not detected
TABLE 13-3
Set 3
Detection
(Normal group)
N.
T. #
Test Date
Sex
Age
Deglycopeptide
Non-glycopeptide
41
N12-218
2012 Mar. 29
M
58
Not detected
Not detected
42
N12-216
2012 Mar. 29
M
46
Not detected
Not detected
43
N12-217
2012 Mar. 29
M
61
Not detected
Not detected
44
N12-219
2012 Mar. 29
M
43
Not detected
Detected
45
N12-220
2012 Mar. 29
M
58
Not detected
Not detected
46
N12-225
2012 Mar. 29
M
58
Not detected
Not detected
47
N12-228
2012 Mar. 29
M
58
Not detected
Not detected
48
N12-229
2012 Mar. 29
M
52
Not detected
Not detected
49
N12-288
2012 Mar. 29
M
53
Not detected
Not detected
50
N12-239
2012 Mar. 29
M
57
Not detected
Not detected
51
N12-249
2012 Mar. 29
M
57
Not detected
Not detected
52
N12-254
2012 Mar. 30
M
56
Not detected
Not detected
53
N12-258
2012 Mar. 30
M
51
Not detected
Not detected
54
N12-261
2012 Mar. 30
M
51
Not detected
Not detected
55
N12-204
2012 Mar. 28
F
44
Not detected
Detected
56
N12-218
2012 Mar. 29
F
59
Not detected
Not detected
57
N12-221
2012 Mar. 29
F
85
Not detected
Not detected
58
N12-226
2012 Mar. 29
F
54
Not detected
Not detected
59
N12-235
2012 Mar. 29
F
53
Detected
Detected
60
N12-241
2012 Mar. 29
F
50
Not detected
Not detected
MRM analysis was performed on 60 HCC samples as described in Example 3. As shown in Tables 14-1 to 14-3, the de-glycosylated peptide (VDFTEIQK) (SEQ ID NO: 9) was detected in 39 samples out of 60 (65.0%). The non-glycosylated peptide (GYQELLEK) (SEQ ID NO: 10) was detected in 32 samples out of 60 samples (53.3%). Based on this, it was determined that the sensitivity to determine the cancer as cancer is 65.0% for the de-glycosylated peptide and 53.3% for the non-glycosylated peptide.
TABLE 14-1
Set 1
Detection
(HCC group)
#
Gender
Age
AFP(0-20)
PIVKA
Virus
Treatment
De-glycopeptide
Non-glycopeptide
1
M
57
8
516
HBV
TACE
Not detected
Not detected
2
M
56
12700
25
HBV
TACE
Detected
Detected
3
M
62
45
30
HBV
RFA
Not detected
Detected
4
M
61
13
NA
HBV
RFA
Not detected
Not detected
5
M
46
13200
189
HBV
TACE & PEIT
Detected
Detected
6
M
64
6
13
HBV
TACE
Not detected
Not detected
7
M
65
6
118
HBV
TACE
Detected
Not detected
8
M
50
6
107
HBV
PEIT
Not detected
Not detected
9
M
57
<5
912
HBV
TACE
Not detected
Detected
10
M
54
337
6604
HBV
TACE(06/1/11)
Detected
Detected
11
M
56
10
NA
HBV
TACE
Not detected
Not detected
12
M
62
2240
37
HBV
PEITT
Detected
Detected
13
M
60
351
644
HBV
TACE
Detected
Detected
14
M
61
34
39
HBV
TACE
Detected
Not detected
15
F
42
283000
1560
HBV
TACE
Detected
Detected
16
F
66
10
41
HBV
RFA
Detected
Not detected
17
F
74
10
74
HBV
TACE, PEIT
Not detected
Detected
18
F
71
<5
675
HBV
TACE
Not detected
Not detected
19
F
61
6
7
HBV
PEIT
Detected
Not detected
20
F
69
473
117
HBV
PEIT
Detected
Detected
TABLE 14-2
Set 2
Detection
(HCC group)
#
Gender
Age
AFP(0-20)
PIVKA
Virus
Treatment
De-glycopeptide
Non-glycopeptide
21
M
70
8
3628
HBV
TACE(06/4/15)
Not detected
Not detected
22
M
47
346
3447
HBV
TACE
Detected
Detected
23
M
49
1690
786
HBV
TACE
Detected
Detected
24
M
61
<5
3
HBV
PEIT
Not detected
Detected
25
M
62
1610
11641
HBV
TACE
Detected
Detected
26
M
66
7
57
HBV
PEIT
Detected
Not detected
27
M
57
73
1270
HBV
TACE
Detected
Detected
28
M
58
360
281
HBV
PEIT
Detected
Detected
29
M
60
164
23
HBV
TACE
Detected
Not detected
30
M
75
3530
1577
HBV
TACE
Detected
Detected
31
M
59
1330
7433
HBV
TACE
Detected
Detected
32
M
44
18
1646
HBV
TACE + PEIT
Not detected
Not detected
33
M
61
12
29
HBV
TACE -> PEI
Not detected
Detected
34
M
59
29
21
HBV
PEIT
Not detected
Not detected
35
F
54
18
61
HBV
PEIT
Not detected
Detected
36
F
63
16
21
HBV
PEIT
Detected
Detected
37
F
51
29
32
HBV
op
Detected
Detected
38
F
63
364
159
HBV
TACE
Detected
Detected
39
F
42
1000
24
HBV
PEIT
Detected
Detected
40
F
63
7
12
HBV
TACE
Detected
Not detected
TABLE 14-3
Set 3
Detection
(HCC group)
#
Gender
Age
AFP(0-20)
PIVKA
Virus
Treatment
De-glycopeptide
Non-glycopeptide
41
M
54
24
19
HBV
PEIT
Detected
Not detected
42
M
58
40300
3522
HBV
TACE
Detected
Detected
43
M
53
217
29
HBV
TACE
Detected
Detected
44
M
56
222000
1969
HBV
TACE
Detected
Detected
45
M
63
6
2706
HBV
TACE
Detected
Not detected
46
M
38
105200
1005
HBV
TACE
Detected
Detected
47
M
55
25
17
HBV
PEIT
Not detected
Detected
48
M
48
7.1
31
HBV
PEIT
Detected
Not detected
49
M
60
7.8
50
HBV
PEIT
Not detected
Not detected
50
M
76
74
5
HBV
PEIT
Detected
Detected
51
M
47
3.2
25
HBV
PEIT
Not detected
Not detected
52
M
58
14.1
34
HBV
PEIT(4/25-16)
Detected
Not detected
53
M
58
350
9
HBV
PEIT
Detected
Not detected
54
M
56
5.5
188
HBV
TACE(6/30)
Not detected
Not detected
55
F
74
15
81
HBV
TACE
Detected
Not detected
56
F
67
43
56
HBV
PEIT
Not detected
Not detected
57
F
56
971
37
HBV
TACE
Detected
Not detected
58
F
46
1088
10
HBV
TACE(3/13)
Detected
Detected
59
F
47
435.6
29
HBV
PEIT
Detected
Not detected
60
F
57
5.8
9
HBV
PEIT(1/1-2)
Not detected
Not detected
The level of AFP was measured in 60 HCC patients using commercially available AFP kit (Bioland; NanoSign AFP, Nanoentech; AFP quantification kit) commonly used in clinics according to the manufacturer's instruction (clinical results). Then the data obtained using AFP kit were compared to the MRM data as described in Example 3 to determine the correlation between the two data set. As shown in
Further to confirm the efficiency of the diagnosis using the present method, ROC (Receiver-Operating Characteristic) curve was determined on 60 normal controls and HCC patients to obtain AUC (Area Under Curve). As a result, it was found that the non-glycosylated peptide (GYQELLEK) (SEQ ID NO: 10) was found to have an AUC value of 0.734, and the de-glycosylated peptide (VDFTEIQK) (SEQ ID NO: 9) was found to have an AUC value of 0.811.
Then the non-glycosylated and de-glycosylated peptides data from AFP protein were combined into one panel using logistic regression model. As a result, it was found that 58 normal people out of 60 were determined as being normal and 2 were determined as having cancer; and 41 liver cancer patients out of 60 were determined as having cancer, and 19 patients were determined as being normal. Thus the accuracy was 82.5%. That is, as shown in Table 15, as a result of comparison of AUC value using the non-glycosylated peptide, de-glycosylated peptide and the combination thereof, the two-peptide panel was found to have a higher value (AUC=0.852) to differentiate liver cancer from normal patients compared to each of the peptide.
This indicates that by monitoring both the non-glycosylated peptide (GYQELLEK) (SEQ ID NO: 10) and the de-glycosylated peptide (VDFTEIQK) (SEQ ID NO: 9) of AFP which were obtained by treating the blood sample of patients with PNGase-F/trypsin, the liver cancer can be differentiated from normal sample with high specificity.
TABLE 15
Predicted group
Normal
Group
group
HCC group
Percent correct
Normal
58
2
96.67%
group
HCC group
19
41
68.33%
Percent of cases correctly classified
82.50%
Three hundred fifty four proteins corresponding to the non-glycosylated peptides selected in Example 2-5, 145 proteins corresponding to 1000 peptides and de-glycosylated peptides, and 182 peptides were applied to individual samples. Then the proteins showing the difference between normal and patient groups were selected as final target protein marker.
In the analysis, normal and patient samples were analyzed alternatively, that is, normal sample No. 1, liver cancer sample No. 1, normal sample No. 2 followed by liver cancer sample No. 2 and the like. The data obtained were fed into Skyline software and analyzed using MedCalc (version 12.2). As a result, 35 proteins showing the difference between the normal and liver cancer sample were selected as follows: Alpha-2-antiplasmin (SERPINF2), Alpha-2-macroglobulin (A2M), Apolipoprotein B-100 (APOB), Beta-galactosidase (GLB1), Bone morphogenetic protein 1 (BMP1), Corticosteroid-binding globulin (SERPINA6), Complement factor H (CFH), Cholinesterase (BCHE), Clusterin (CLU), Collagen alpha-1(XII) chain (COL12A1), Carboxypeptidase N subunit 2 (CPN2), Versican core protein (VCAN), Receptor tyrosine-protein kinase erbB-3 (ERBB3), Coagulation factor V (F5), Coagulation factor XI (F11), Follistatin-related protein 1 (FSTL1), N-acetylglucosamine-6-sulfatase (GNS), G-protein coupled receptor 126 (GPR126), Heparin cofactor 2 (SERPIND1), Hypoxia up-regulated protein 1 (HYOU1), Integrin alpha-2 (ITGA2), Integrin alpha-3 (ITGA3), Integrin alpha-6 (ITGA6), Integrin alpha-M (ITGAM), Integrin beta-2 (ITGB2), Plasma kallikrein (KLKB1), Kinectin (KTN1), Lysosome-associated membrane glycoprotein 2 (LAMP2), Galectin-3-binding protein (LGALS3BP), Plexin-A1 (PLXNA1), Periostin (POSTN), Inactive tyrosine-protein kinase 7 (PTK7), Roundabout homolog 4 (ROBO4), Tenascin (TNC), Vitronectin (VTN)
The ROC curves were drawn for each of the 35 target proteins. A ROC curve is a graphical plot that illustrates the changing relationship between the specificity and sensitivity. In ROC curves, bigger AUC (area under curve) value indicates better diagnosis ability. The AUC values determined were listed in Table 16-1 and 16-2. ROC curve and the correlation plot were prepared using MedCalc (version 12.2) statistical program.
TABLE 16-1
AUC-value
Precursor
Precursor
Product
Product
Fragment
Normal vs.
N.
Protein Name
Peptide Sequence
SEQ ID NO
Mz
Charge
Mz
Charge
Ion
HCC
1
Alpha-2-antiplasmin
LGNQEPGGQTALK
(SEQ ID NO: 12)
656.8
2
771.4
1
Y8
0.796
(SERPINF2)
NPDPSAPR
(SEQ ID NO: 11)
427.2
2
527.3
1
y5
0.799
2
Alpha-2-
AIGYLNTGYQR
(SEQ ID NO: 14)
628.3
2
738.4
1
y6
0.941
macroglobulin
FEVQVTVPK
(SEQ ID NO: 15)
523.8
2
244.2
1
y2
0.938
(A2M)
IAQWQSFQLEGGLK
(SEQ ID NO: 16)
802.9
2
978.5
1
y9
0.941
NEDSLVFVQTDK
(SEQ ID NO: 17)
697.8
2
737.4
1
y6
0.934
VSDQTLSLFFTVLQDVPVR
(SEQ ID NO: 13)
1082.6
2
1320.7
1
y11
0.861
VSVQLEASPAFLAVPVEK
(SEQ ID NO: 18)
942.5
2
472.3
1
y4
0.852
3
Apolipoprotein
FEVDSPVYDATWSASLK
(SEQ ID NO: 19)
958.0
2
1337.7
1
y12
0.526
B-100 (APOB)
LSLESLTSYFSIESSTK
(SEQ ID NO: 20)
946.5
2
1249.6
1
y11
0.707
4
Beta-galactosidase
NNVITLDITGK
(SEQ ID NO: 21)
594.3
2
655.4
1
b6
0.857
(GLB1)
VNYGAYINDFK
(SEQ ID NO: 22)
652.3
2
870.4
1
y7
0.912
5
Bone morphogenetic
GIFLDTIVPK
(SEQ ID NO: 24)
551.8
2
672.4
1
y6
0.916
protein 3 (BMP1)
IILDFTSLDLYR
(SEQ ID NO: 23)
734.9
2
703.4
1
b6
0.556
6
Corticosteroid-
AQLLQGLGFDLTER
(SEQ ID NO: 25)
780.9
2
928.5
1
b9
0.815
binding globulin
ITQDAQLK
(SEQ ID NO: 26)
458.8
2
215.1
1
b2
0.524
(SERPINA6)
WSAGLTSSQVDLYIPK
(SEQ ID NO: 27)
883.0
3
357.2
1
y3
0.519
7
Complement factor
SPDVIDGSPISQK
(SEQ ID NO: 28)
671.8
2
831.4
1
y8
0.531
H (CFH)
SSIDIENGFISESQYTYALK
(SEQ ID NO: 29)
1133.0
2
1076.5
1
b10
0.853
8
Cholinesterase
AILQSGSFNAPWAYTSLYEAR
(SEQ ID NO: 31)
1141.1
2
1292.7
1
y11
0.745
(BCHE)
IFFPGVSEFGK
(SEQ ID NO: 32)
614.3
2
261.2
1
b2
0.745
WSDIWDATK
(SEQ ID NO: 30)
561.3
2
935.4
1
y8
0.703
YLTLNTESTR
(SEQ ID NO: 33)
599.3
2
921.5
1
y8
0.789
9
Clusterin (CLU)
ASSIIDELFQDR
(SEQ ID NO: 35)
697.4
2
922.4
1
y7
0.826
EIQNAVGVK
(SEQ ID NO: 36)
536.3
2
701.4
1
y7
0.766
LADLTQGEDQYYLR
(SEQ ID NO: 102)
842.9
2
1043.5
1
y8
0.842
10
Collagen alpha-1
ITEVTSEGFR
(SEQ ID NO: 38)
569.8
2
696.3
1
y6
0.586
(XII) chain
NVQVYDPTPNSLDVR
(SEQ ID NO: 37)
858.9
2
800.4
1
y7
0.882
(COL12A1)
VQISLVQYSR
(SEQ ID NO: 39)
506.8
2
652.3
1
y5
0.628
VYDPSTSTLNVR
(SEQ ID NO: 40)
676.3
2
689.4
1
y6
0.522
11
Carboxypeptidase N
AFGSNPDLTK
(SEQ ID NO: 41)
525.3
2
831.4
1
y8
0.671
subunit 2
LELLSLSK
(SEQ ID NO: 42)
451.8
2
243.1
1
b2
0.837
(CPN2)
TABLE 16-2
AUC-value
Precursor
Precursor
Product
Product
Fragment
Normal
N.
Protein name
Peptide Sequence
SEQ ID NO
Mz
Charge
Mz
Charge
Ion
vs. HCC
12
Versican core protein
LLASDAGLYR
(SEQ ID NO: 44)
539.8
2
694.4
1
y6
0.907
TDGQVSGEAIK
(SEQ ID NO: 45)
552.8
2
517.3
1
y5
0.888
VVAEDITQTSR
(SEQ ID NO: 43)
609.8
2
514.3
1
b5
0.608
13
Receptor tyrosine-protein
LAEVPDLLEK
(SEQ ID NO: 47)
563.8
2
413.2
1
b4
0.529
kinase erbB-3 (ERBB3)
NLDVTSLGFR
(SEQ ID NO: 46)
561.3
2
543.3
1
b5
0.851
14
Coagulation
ASEFLGYWEPR
(SEQ ID NO: 49)
677.8
2
272.2
1
y2
0.763
factor V (F5)
TWDQSIALR
(SEQ ID NO: 48)
545.3
2
731.3
1
b6
0.655
15
Coagulation factor
LSSDGSPTK
(SEQ ID NO: 50)
446.2
2
691.3
1
y7
0.947
XI (F11)
VVSGFSLK
(SEQ ID NO: 51)
418.7
2
286.2
1
b3
0.936
16
Follistatin-related
GSDYSEILDK
(SEQ ID NO: 52)
563.8
2
867.4
1
y7
0.755
protein 1
LSFQEFLK
(SEQ ID NO: 53)
506.3
2
201.1
1
b2
0.593
17
N-acetylglucosamine-6-
AFQNVFAPR
(SEQ ID NO: 55)
525.3
2
343.2
1
y3
0.914
sulfatase (GNS)
YYDYTLSINGK
(SEQ ID NO: 54)
668.8
2
732.4
1
y7
0.781
18
G-protein coupled
ISVVIQNILR
(SEQ ID NO: 57)
577.9
2
515.3
1
y4
0.703
receptor
SLSSSSIGSDSTYLTSK
(SEQ ID NO: 56)
860.4
2
1008.4
1
b11
0.708
126 (GPR126)
VILPQTSDAYQVSVAK
(SEQ ID NO: 58)
860.0
2
404.3
1
y4
0.710
19
Heparin cofactor 2
DFVDASSK
(SEQ ID NO: 59)
434.7
2
362.2
1
b3
0.578
EYYFAEAQIADFSDPAFISK
(SEQ ID NO: 60)
1156.5
2
662.4
1
y6
0.706
NYNLVESLK
(SEQ ID NO: 61)
540.3
2
802.5
1
y7
0.918
SVNDLYIQK
(SEQ ID NO: 62)
540.3
2
187.1
1
b2
0.900
TLEAQLTPR
(SEQ ID NO: 63)
514.8
2
814.4
1
y7
0.894
20
Hypoxia up-regulated
DEPGEQVELK
(SEQ ID NO: 66)
572.3
2
260.2
1
y2
0.711
protein 1 (HYOU1)
VFGSQDLTTVK
(SEQ ID NO: 64)
597.8
2
519.3
1
b5
0.936
VIDETWAWK
(SEQ ID NO: 65)
574.3
2
691.4
1
y5
0.885
21
Integrin alpha-2
FGIAVLGYLNR
(SEQ ID NO: 68)
611.9
2
488.3
1
b5
0.726
(ITGA2)
YFFDVSDEAALLEK
(SEQ ID NO: 67)
823.9
2
1189.6
1
y11
0.771
22
Integrin alpha-3
DITIVTGAPR
(SEQ ID NO: 69)
521.8
2
501.3
1
y5
0.825
(ITGA3)
TVEDVGSPLK
(SEQ ID NO: 70)
522.8
2
201.1
1
b2
0.530
23
Integrin alpha-6
LPNAGTQVR
(SEQ ID NO: 72)
478.3
2
396.2
1
b4
0.704
(ITGA6)
LWDSTFLEEYSK
(SEQ ID NO: 71)
759.4
2
915.4
1
y7
0.588
24
Integrin alpha-M
EFDVTVTVR
(SEQ ID NO: 73)
533.3
2
491.2
1
b4
0.540
(ITGAM)
ILVVITDGEK
(SEQ ID NO: 74)
543.8
2
425.3
1
b4
0.916
25
Integrin beta-2
ALNEITESGR
(SEQ ID NO: 76)
545.3
2
662.3
1
y6
0.912
(ITGB2)
LTDNSNQFQTEVGK
(SEQ ID NO: 75)
790.9
2
661.4
1
y6
0.660
YLIYVDESR
(SEQ ID NO: 103)
579.3
2
506.2
1
y4
0.726
26
Plasma kallikrein
DSVTGTLPK
(SEQ ID NO: 78)
459.3
2
244.2
1
y2
0.847
(KLKB1)
GVNFDVSK
(SEQ ID NO: 77)
433.2
2
709.4
1
y6
0.917
IAYGTQGSSGYSLR
(SEQ ID NO: 79)
730.4
2
826.4
1
y8
0.857
YSPGGTPTAIK
(SEQ ID NO: 80)
546.3
2
841.5
1
y9
0.912
27
Kinectin (KTN1)
LQTLVSEQPNK
(SEQ ID NO: 82)
628.8
2
242.1
1
b2
0.941
TEDSSLTK
(SEQ ID NO: 81)
440.7
2
520.2
1
b5
0.634
28
Lysosome-associated
GILTVDELLAIR
(SEQ ID NO: 84)
656.9
2
472.3
1
y4
0.693
membrane glycoprotein 2
VQPFDVTQGK
(SEQ ID NO: 83)
559.8
2
587.3
1
b5
0.909
29
Galectin-3-binding
ALGFFDATQALGR
(SEQ ID NO: 85)
674.8
2
960.5
1
y9
0.920
protein (LGALS3BP)
ELSEALGQIFDSQR
(SEQ ID NO: 86)
796.9
2
950.5
1
y8
0.914
SDLAVPSELALLK
(SEQ ID NO: 87)
678.4
2
870.5
1
y8
0.898
YSSDYFOAPSDYR
(SEQ ID NO: 88)
799.8
2
338.2
1
y2
0.883
30
Plexin-A1 (PLXNA1)
LSLPWLLNK
(SEQ ID NO: 90)
542.3
2
314.2
1
b3
0.547
YDYTEDPTILR
(SEQ ID NO: 89)
693.3
2
714.4
1
y6
0.949
31
Periostin (POSTN)
EVDDTLLVNELK
(SEQ ID NO: 91)
694.4
2
602.4
1
y5
0.614
IIDGVPVEITEK
(SEQ ID NO: 92)
656.9
2
1086.6
1
y10
0.914
32
Inactive tyrosine-protein
SADASFNIK
(SEQ ID NO: 93)
476.7
2
679.4
1
y6
0.762
kinase 7 (PTK7)
SSLQPITTLGK
(SEQ ID NO: 94)
572.8
2
416.2
1
b4
0.815
33
Roundabout homolog 4
DLSQSPGAVPQALVAWR
(SEQ ID NO: 95)
898.0
2
715.4
1
y6
0.516
GPDSNVLLLR
(SEQ ID NO: 96)
542.3
2
514.4
1
y4
0.909
34
Tenascin (TNC)
APTAQVESFR
(SEQ ID NO: 98)
553.3
2
765.4
1
y6
0.777
LLETVEYDISGAER
(SEQ ID NO: 97)
797.9
2
556.1
1
b5
0.888
35
Vitronectin (VTN)
DGSLFAFR
(SEQ ID NO: 99)
456.7
2
540.3
1
y4
0.705
DVWGIEGPIDAAFTR
(SEQ ID NO: 100)
823.9
2
458.2
1
b4
0.774
FEDGVLDPDYPR
(SEQ ID NO: 101)
711.8
2
647.3
1
y5
0.712
The various singular/plural permutations may be expressly set forth herein for sake of clarity. Although a few embodiments of the present disclosure have been shown and described, it would be appreciated by those skilled in the art that changes may be made in this embodiment without departing from the principles and sprit of the invention, the scope of which is defined in the claims and their equivalents.
Unless defined or interpreted otherwise, all technical and scientific terms and any acronyms used herein have the same meanings as commonly understood by one of ordinary skill in the art in the field of the invention.
Kim, Hyunsoo, Kim, Youngsoo, Jin, Jonghwa, Kim, Kyunggon, Yoon, Jung-Hwan
| Patent | Priority | Assignee | Title |
| 10697971, | Apr 20 2017 | Korea Basic Science Institute | Diagnostic method of liver cancer using α-fetoprotein derived glycopeptides by mass spectrometry |
| Patent | Priority | Assignee | Title |
| 20060269980, | |||
| 20070269895, | |||
| 20150346194, | |||
| KR1020100120788, | |||
| KR1020120125157, |
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